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llama.cpp
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Fix lambda capture

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Ed Addario 2025-10-20 22:04:35 +01:00
parent 543b5a99db
commit 27bf25e93c
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1 changed files with 3 additions and 3 deletions
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src/llama-quant.cpp
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@ -690,7 +690,7 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
#endif
};
constexpr double epsilon = 1e-12;
const double epsilon = 1e-12;
constexpr double infinity = std::numeric_limits<double>::infinity();
constexpr uint32_t file_magic = 0x42505731; // BPW1
const char * func = __func__;
@ -1118,7 +1118,7 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
};
// Returns lambda per slice or 0.0 if no activations
auto estimate_lambda = [](const float * values, const float * activations, const int64_t n_per_row, const int64_t ne2) -> std::vector<float> {
auto estimate_lambda = [&](const float * values, const float * activations, const int64_t n_per_row, const int64_t ne2) -> std::vector<float> {
const int64_t ns = std::max<int64_t>(1, ne2);
std::vector<float> lambdas(ns, 0.0f);
if (!activations) { return lambdas; }
@ -1421,7 +1421,7 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
}
// Keep only the pareto‑optimal candidates and enforce convexity in (bytes, error) curve
auto pareto_convex = [epsilon](std::vector<candidate_types> & candidates) {
auto pareto_convex = [&](std::vector<candidate_types> & candidates) {
if (candidates.empty()) { return; }
std::sort(candidates.begin(), candidates.end(), [](const candidate_types & a, const candidate_types & b) {